Zachary Depp, Halit Bugra Tulay, C. Emre Koksal (The Ohio State University)

The traditional vehicular roll-jam attack is an effective means to gain access to the target vehicle by jamming and recording key fob inputs from a victim. However, it requires specific knowledge of the attack surface, and delicate tuning of software-defined radio parameters. We have developed an enhanced version of the roll-jam attack that uses a known noise signal for jamming, in contrast to the additive white Gaussian noise that is typically used in the attack. Using a known noise signal allows for less strict tuning of the software-defined radios used in the attack, and allows for digital noise removal of the recorded input to enhance the replay attack.

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RAI2: Responsible Identity Audit Governing the Artificial Intelligence

Tian Dong (Shanghai Jiao Tong University), Shaofeng Li (Shanghai Jiao Tong University), Guoxing Chen (Shanghai Jiao Tong University), Minhui Xue (CSIRO's Data61), Haojin Zhu (Shanghai Jiao Tong University), Zhen Liu (Shanghai Jiao Tong University)

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Brokenwire: Wireless Disruption of CCS Electric Vehicle Charging

Sebastian Köhler (University of Oxford), Richard Baker (University of Oxford), Martin Strohmeier (armasuisse Science + Technology), Ivan Martinovic (University of Oxford)

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Drone Security and the Mysterious Case of DJI's DroneID

Nico Schiller (Ruhr-Universität Bochum), Merlin Chlosta (CISPA Helmholtz Center for Information Security), Moritz Schloegel (Ruhr-Universität Bochum), Nils Bars (Ruhr University Bochum), Thorsten Eisenhofer (Ruhr University Bochum), Tobias Scharnowski (Ruhr-University Bochum), Felix Domke (Independent), Lea Schönherr (CISPA Helmholtz Center for Information Security), Thorsten Holz (CISPA Helmholtz Center for Information Security)

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RCABench: Open Benchmarking Platform for Root Cause Analysis

Keisuke Nishimura, Yuichi Sugiyama, Yuki Koike, Masaya Motoda, Tomoya Kitagawa, Toshiki Takatera, Yuma Kurogome (Ricerca Security, Inc.)

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